NSF EPSCoR and the Role of Cyberinfrastructure

1. NSF EPSCoR and the Role of Cyberinfrastructure Dr. Jennifer M. Schopf National Science Foundation EPSCoR Office October 6, 2010

2. Outline • CyberInfrastructure for 21st Century Vision • CyberInfrastructure within EPSCoR • Networking • Data Sharing • Collaboration

3. Research Is Changing • Geographically distributed user communities • Numerous labs, universities, industry • Integration with other national resources • Inevitably multi-agency, multi-disciplinary • Extremely large quantities of data • Petabyte data sets, with complex access patterns • Also thousands of SMALL data sets • None of it tagged as you need it, or in the right format

4. Framing the QuestionScience has been Revolutionized by CI • Modern science • Data- and compute-intensive • Integrative • MultiscaleCollabs • Add’l complexity • Individuals, groups, teams, communities • Must Transition NSF CI approach to address these issues

5. What is Needed?An ecosystem, not components… NSF-wide CI Framework for 21st Century Science & Engineering People, Sustainability, Innovation, Integration

6. CyberInfrastructure Ecosystem Organizations Universities, schools Government labs, agencies Research and Med Centers Libraries, Museums Virtual Organizations Communities Expertise Research and Scholarship Education Learning and Workforce Development Interoperability and ops Cyberscience Scientific Instruments Large Facilities, MREFCs,telescopes Colliders, shake Tables Sensor Arrays - Ocean, env’t, weather, buildings, climate. etc Discovery Collaboration Education Data Databases, Data reps, Collections and Libs Data Access; stor., nav mgmt, mining tools, curation Computational Resources Supercomputers Clouds, Grids, Clusters Visualization Compute services Data Centers Networking Campus, national, international networks Research and exp networks End-to-end throughput Cybersecurity Software Applications, middleware Software dev’t & support Cybersecurity: access, authorization, authen. Sustain, Advance, Experiment

7. Cyberinfrastructure Framework for the 21st century (CF21) • High-end computation, data, visualization for transformative science • Facilities/centers as hubs of innovation • MREFCs and collaborations including large-scale NSF collaborative facilities, international partners • Software, tools, science applications, and VOs critical to science, integrally connected to instruments • Campuses fundamentally linked end-to-end; grids, clouds, loosely coupled campus services, policy to support • People Comprehensive approach workforce development for 21st century science and engineering

8. Data (Viz) ACCITask Forces Campus Bridging Dan Atkins Tony Hey Craig Stewart • Timelines: 12-18 months • Advising NSF • Workshop(s) • Recommendations • Input to NSF informs • CF21 programs • 2011-2 CI Vision Plan Software Computing (Clouds Grids) David Keyes Valerie Taylor Thomas Zacharia Education Workforce GC & VOs Alex Ramerez Tinsley Oden

9. Preliminary Task Force (TF) Results • Computing TF Workshop Interim Report • Rec: Address sustainability, people, innovation • Software TF Interim Report • Rec: Address sustainability, create long term, multi-directorate, multi-level software program • GCC/VO TF Interim Report • Rec: Address sustainability, OCI to nurture computational science across NSF units • Software Sustainability WS (Campus Bridging) • Rec: Open source, use sw eng practices, reproducibility

10. CF21 Strategy • Driven by science and engineering • Intense coupling of data, sensors, satellites, computing, visualization, grids, software, VOs; entire CI ecosystem • Better campus integration • Major Facilities CI planning • Task Forces and research community provides guidance and input • All NSF Directorates involved • Sustain, Advance, Experiment 12

11. EPSCoR and CI

12. EPSCoR Origins • NSF’s 1979 statutory authority “authorizes the Director to operate an Experimental Program to Stimulate Competitive Research (EPSCoR) to assist less competitive states” that: • Have historically received little federal R&D funding; and • Have demonstrated a commitment to develop their research bases and improve science and engineering research and education programs at their universities and colleges.

13. EPSCoR • Purpose/Objectives: • Build research capacity and competitiveness • Broaden individual and institutional participation in STEM • Promote development of a technically engaged workforce • Foster collaborative partnerships • Support state-wide programs

15. Stats: In the 29 Jurisdictions… • 21% of the nation’s total population • 24% of the research institutions • 16% of the employed scientists and engineers • Receive about 12% of all NSF research funding.

16. EPSCoR 2020 • In 2006 workshop and follow-on report made a number of recommendations • Refocusing for EPSCoR • Vision for moving forward in the context of collaborative science • 6 Recommendations http://www.nsf.gov/od/oia/programs/epscor/docs/ EPSCoR_2020_Workshop_Report.pdf

17. Recc 1: More Flexible ResearchInfrastructure and Improvement Awards • 2008- Raised duration to 5 years • 2009 – Raised funding to $4M per year • Additional programs were offered

18. Sub-Recommendation • Ensure that all EPSCoR jurisdictions have the CI necessary to attract and execute advance research • Specifically to attract (and train) the next generation workforce

19. A Related Study: • Amy Apon, U. Arkansas • “Demonstrating the Impact of High Performance Computing to Academic Competiveness” • Investigating correlation between • University investment in CI • In this case, was there a machine in the “Top 500” • Research productivity measures • NSF Funding, federal funding, publications, etc

20. Without HPC Investment With HPC Investment Avg NSF funding: $30,354,000 Avg NSF funding: $7,781,000 FY06: 95 of Top NSF-funded Universities with HPC 98 of Top NSF-funded Universities without HPC Amy Apon, aapon@uark.edu

21. Caveats • Correlation not causation • Open question if these are the right things to measure • Dr. Apon herself says this is very preliminary • But follow on work is fascinating • Another open question – how do we measure return on investment?

22. CI in EPSCoR • Networking • Data Sharing • Collaboration

23. Research Infrastructure Improvement Awards (RII) Cyber Connectivity (C2) • Up to 2 years and $1M • Support inter-campus and intra-campus cyber connectivity and broadband • Across a EPSCoR jurisdiction • In FY10: 23 Props Rec’d; 17 Funded (ARRA) • In FY 11: 12 eligible jurisdictions

24. Networking can… • Support applications accessing remote data sources • Support educational opportunities • Support collaborations • SUPPORT SCIENCE!

25. Data Sharing • To support collaborations, cross- disciplinary, transformational research, curation of data is the keystone

26. Digital resources that are not properly curated do not remain accessible for long Source: Koehler W. (2004) Information Research, 9 (2), 174

27. Digital resources that are not properly curated do not remain accessible for long Source: Koehler W. (2004) Information Research, 9 (2), 174

28. Poor Data Practices Time of publication Specific details General details Retirement or career change Information Content Accident Death Time (Michener et al. 1997)

29. The Shift Towards DataImplications • All science is becoming data-dominated • Experiment, computation, theory • Totally new methodologies • Algorithms, mathematics • All disciplines from science and engineering to arts and humanities • End-to-end networking becomes critical part of CI ecosystem • Campuses, please note! • How do we train “data-intensive” scientists? • Data policy becomes critical!

30. Long Standing NSF Data Policy “Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing.” Has not been widely enforced, with a few exceptions like OCE NSF Proposal and Award Policy and Procedure Guide, Award and Administration Guideline PDF page 61 http://www.nsf.gov/pubs/policydocs/pappguide/nsf10_1/aagprint.pdf

31. Changing Data Management PolicyIMPLEMENTATION • Planning underway for 2+ years within NSF • May 5, 2010 National Science Board meeting • Change in the implementation of the existing policy on sharing research data discussed • Oct 1, 2010 • Change in the NSF GPG released http://www.nsf.gov/news/news_summ.jsp?cntn_id=116928&WT.mc_id=USNSF_51 http://news.sciencemag.org/scienceinsider/2010/05/nsf-to-ask-every-grant-applicant.html

32. As of January 2011: • All proposals must include a data management plan • Two-page supplementary document • Can request budget to cover costs • Echos the actions of other funding agencies • NIH, NASA, NOAA, EU Commission http://www.nsf.gov/pubs/policydocs/pappguide/nsf11001/gpg_index.jsp

33. Guidelines will beCommunity Driven • Avoid a one-size-fits-all approach • Different disciplines encourage the approaches to data-sharing as acceptable within those discipline cultures • Data management plans will be subject to peer review, community standards • Flexibility at the directorate and division levels • Tailor implementation as appropriate • Request additional funding to implement their data management plan

34. DMP cont. • DMP may include only the statement that no detailed plan is needed • Statement must be accompanied by a clear justification • DMP will be reviewed as an integral part of the proposal, coming under Intellectual Merit or Broader Impacts or both, as appropriate for the scientific community of relevance

35. Directorate, Office, Program Specific Requirements http://www.nsf.gov/bfa/dias/policy/dmp.jsp • If guidance specific to the program is not available, then the requirements in GPG apply • Individual solicitations may have additional requirements as well

36. One More Thing to Keep In Mind • This policy mandates that you have to make your data accessible • Archive, open access, metadata tagged • This is actually the easy step • Getting the data out again, using other people’s data – a MUCH harder problem • But not part of this work

37. Collaborations

38. Research Infrastructure Improvement Awards (RII) Track 1 • Up to 5 years and $20M • Improve physical and human infrastructure critical to R&D competitiveness • Priority research aligned with jurisdiction S&T plan • In FY 2009: 9 Proposals Received; 6 Funded • In FY 2010: 14 Proposals Rcv’d; 7 Funded • In FY 2011: 7 eligible jurisdictions

39. Research Infrastructure Improvement Awards (RII) Track 2 • Up to 3 years and $6M • Consortia of jurisdictions • Support innovation-enabling cyberinfrastructure • Regional, thematic, or technological importance to suite of jurisdictions • In FY 09: 9 Props Rec’d; 7 Funded (5 ARRA) • In FY10: 9 Props Rec’d; 5 Funded • In FY11: 6 eligible jurisdictions

40. Collaborations • Support the jurisdiction S&T plans • Includes industry involvement • Support the jurisdiction CI plan • Support research and education across the jurisdiction • Including community colleges, tribal colleges, PUI’s, and others • Support workforce development, external outreach

41. Research Is Changing • Geographically distributed user communities • Numerous labs, universities, industry • Integration with other national resources • Inevitably multi-agency, multi-disciplinary • Extremely large quantities of data • Petabyte data sets, with complex access patterns • Also thousands of SMALL data sets • None of it tagged as you need it, or in the right format • EPSCoR and NSF are growing and changing to support new science

42. More Information • Jennifer M. Schopf • jschopf@nsf.gov • jms@nsf.gov • Dear Colleague letter for CF21 http://www.nsf.gov/pubs/2010/nsf10015/nsf10015.jsp